2 citations · 2 across the 4 of their papers we have counts for
4 papers
Spatio-Sequential Recurrent Network for 3-D Tunnel Propagation Modeling
Jiahao Li, Jingxin Xue, Keqi Ni +4
Fine-mesh parabolic wave equation (PWE) simulations are high-fidelity but time-consuming, which limits real-time tunnel propagation analysis and motivates coarse-to-fine reconstruc…
Physics-Informed Deep Recurrent Back-Projection Network for Tunnel Propagation Modeling
Kunyu Wu, Qiushi Zhao, Jingyi Zhou +4
Accurate and efficient modeling of radio wave propagation in railway tunnels is is critical for ensuring reliable communication-based train control (CBTC) systems. Fine-grid parabo…
Intelligent Optimization of Wireless Access Point Deployment for Communication-Based Train Control Systems Using Deep Reinforcement Learning
Kunyu Wu, Qiushi Zhao, Zihan Feng +4
Urban railway systems increasingly rely on communication based train control (CBTC) systems, where optimal deployment of access points (APs) in tunnels is critical for robust wirel…
Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey
Junqiao Wang, Zeng Zhang, Yangfan He +18
With the rapid evolution of large language models (LLM), reinforcement learning (RL) has emerged as a pivotal technique for code generation and optimization in various domains. Thi…